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Photonics
Special Issues
High-Performance Optical Coherence Tomography
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High-Performance Optical Coherence Tomography

A special issue of Photonics (ISSN 2304-6732).

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 3708

Special Issue Editors

Dr. Dongmei Huang

E-Mail Website
Guest Editor
Photonics Research Institute, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: optical coherence tomography; fiber lasers; swept lasers; nonlinear optics; fiber sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Peng Xiao

E-Mail Website
Guest Editor
Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China
Interests: optical coherence tomography; ophthalmic imaging; biomedical optics; optical instrumentation; intelligent image analysis
Dr. Zhenhe Ma

E-Mail Website
Guest Editor
School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China
Interests: optical detection; optical coherence tomography; photoacoustic imaging; spectrum analysis; deep learning
Dr. Lev A. Matveev

E-Mail Website
Guest Editor
Institute of Applied Physics of the RAS, 46 Ulyanova St., Nizhny Novgorod 603950, Russia
Interests: signal and image processing; statistical machine learning; Monte Carlo and analytic simulations; optical coherence tomography; angiography; elastography; multimodal imaging; medical imaging
Prof. Dr. Alex Vitkin

E-Mail Website
Guest Editor
1. Department of Medical Biophysics & Radiation Oncology, University of Toronto, Toronto, ON M5S 3K1, Canada
2. Division of Biophysics and Bioimaging, Ontario Cancer Institute, University Health Network, Toronto, ON M5G 2M9, Canada
Interests: optical coherence tomography; optical polarization effects in tissues; functional tissue assessment; laser–tissue interactions; radiation oncology physics; radiobiology

Special Issue Information

Dear Colleagues,

Optical coherence tomography (OCT) is a representative case of the successful commercialization of an optical technique. It has been adopted in not only medical diagnostics but also in industrial inspection and model construction. Along with technological development, high-performance next-generation OCT systems continues to emerge, such as swept source OCT (SS-OCT), full-field OCT (FFOCT), OCT angiography (OCTA) and other functional OCT systems. These promising OCT techniques are of great interest in both academic research and practical applications with technical features of high resolution, high imaging speed, large imaging range, or offering specific functional information. Meanwhile, the performance of these OCT systems are significantly related with the improvement of key system or technical modules like swept lasers, demodulation technology, image processing algorithm, etc.

This Special Issue aims to bring together researchers working on all aspects of high-performance next-generation OCT, both systems and technological developments, from basic research to in-orbit results. Novel OCT system development and special applications in medical and industrial areas are welcome. Techniques for the generation of high-performance swept laser with high sweep speed, wideband sweep range, and high coherence, signal and image processing algorithms are also invited.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Research works on high-performance OCT system like SSOCT, FFOCT, OCTA, Dynamic OCT, Doppler OCT, etc., including optimization methods for the imaging system, algorithm optimization for improving the resolution, imaging range, and special applications in medical diagnostics, industrial inspection, and model construction.

Research works on novel techniques for generating swept lasers, including Fourier domain mode locked laser, time-stretched swept laser, swept laser based on frequency shift, dispersion tuning swept laser, short cavity swept laser based on MEMS;

We look forward to receiving your contributions.

Dr. Dongmei Huang
Dr. Peng Xiao
Dr. Zhenhe Ma
Dr. Lev A. Matveev
Prof. Dr. Alex Vitkin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optical coherence tomography
  • biomedical optical imaging
  • optical technology
  • fiber lasers
  • swept lasers

Published Papers (2 papers)

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Research

18 pages, 7233 KiB  
Article
A Lightweight Swin Transformer-Based Pipeline for Optical Coherence Tomography Image Denoising in Skin Application
by Jinpeng Liao, Chunhui Li and Zhihong Huang
Photonics 2023, 10(4), 468; https://doi.org/10.3390/photonics10040468 - 19 Apr 2023
Cited by 5 | Viewed by 1741
Abstract
Optical coherence tomography (OCT) has attracted attention in dermatology applications for skin disease characterization and diagnosis because it provides high-resolution (<10 μm) of tissue non-invasively with high imaging speed (2–8 s). However, the quality of OCT images can be significantly degraded by speckle [...] Read more.
Optical coherence tomography (OCT) has attracted attention in dermatology applications for skin disease characterization and diagnosis because it provides high-resolution (<10 μm) of tissue non-invasively with high imaging speed (2–8 s). However, the quality of OCT images can be significantly degraded by speckle noise, which results from light waves scattering in multiple directions. This noise can hinder the accuracy of disease diagnosis, and the conventional frame averaging method requires multiple repeated (e.g., four to six) scans, which is time consuming and introduces motion artifacts. To overcome these limitations, we proposed a lightweight U-shape Swin (LUSwin) transformer-based denoising pipeline to recover high-quality OCT images from the noisy OCT images by utilizing a fast one-repeated OCT scan. In terms of the peak signal-to-noise-ratio (PSNR) performance, the results reveal that the denoised images from the LUSwin transformer (26.92) are of a higher quality than the four-repeated frame-averaging method (26.19). Compared to the state-of-the-art networks in image denoising, the proposed LUSwin transformer has the smallest floating points operation (3.9299 G) and has the second highest PSNR results, only 0.02 lower than the Swin-UNet, which has the highest PSNR results (26.94). This study demonstrates that the transformer model has the capacity to denoise the noisy OCT image from a fast one-repeated OCT scan. Full article
(This article belongs to the Special Issue High-Performance Optical Coherence Tomography)
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19 pages, 5025 KiB  
Article
A Novel Intraretinal Layer Semantic Segmentation Method of Fundus OCT Images Based on the TransUNet Network Model
by Zhijun Gao, Zhiming Wang and Yi Li
Photonics 2023, 10(4), 438; https://doi.org/10.3390/photonics10040438 - 12 Apr 2023
Cited by 5 | Viewed by 1541
Abstract
Optical coherence tomography (OCT) is used to obtain retinal images and stratify them to obtain the thickness of each intraretinal layer, which plays an important role in the clinical diagnosis of many ophthalmic diseases. In order to overcome the difficulties of layer segmentation [...] Read more.
Optical coherence tomography (OCT) is used to obtain retinal images and stratify them to obtain the thickness of each intraretinal layer, which plays an important role in the clinical diagnosis of many ophthalmic diseases. In order to overcome the difficulties of layer segmentation caused by uneven distribution of retinal pixels, fuzzy boundaries, unclear texture, and irregular lesion structure, a novel lightweight TransUNet deep network model was proposed for automatic semantic segmentation of intraretinal layers in OCT images. First, ResLinear-Transformer was introduced into TransUNet to replace Transformer in TransUNet, which can enhance the receptive field and improve the local segmentation effect. Second, Dense Block was used as the decoder of TransUNet, which can strengthen feature reuse through dense connections, reduce feature parameter learning, and improve network computing efficiency. Finally, the proposed method was compared with the state-of-the-art on the public SD-OCT dataset of diabetic macular edema (DME) patients released by Duke University and POne dataset. The proposed method not only improves the overall semantic segmentation accuracy of retinal layer segmentation, but also reduces the amount of computation, achieves better effect on the intraretinal layer segmentation, and can better assist ophthalmologists in clinical diagnosis of patients. Full article
(This article belongs to the Special Issue High-Performance Optical Coherence Tomography)
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